scholarly journals Neuro-Computational Foundations of Moral Preferences

2019 ◽  
Author(s):  
Giuseppe Ugazio ◽  
Marcus Grueschow ◽  
Rafael Polania ◽  
Claus Lamm ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Human Life ◽  
Neural Mechanisms ◽  
Common Currency ◽  
Moral Value ◽  
Neural Representations ◽  
Behavioral Paradigm ◽  
The Common ◽  
Decision Mechanisms

AbstractMoral preferences pervade many aspects of our lives, dictating how we ought to behave, whom we can marry, and even what we eat. Despite their relevance, one fundamental question remains unanswered: Where do individual moral preferences come from? It is often thought that all types of preferences reflect properties of domain-general neural decision mechanisms that employ a common “neural currency” to value choice options in many different contexts. This assumption, however, appears at odds with the observation that many humans consider it intuitively wrong to employ the same scale to compare moral value (e.g., of a human life) with material value (e.g., of money). In this paper, we directly challenge the common-currency hypothesis by comparing the neural mechanisms that represent moral and financial subjective values. In a study combining fMRI with a novel behavioral paradigm, we identify neural representations of the subjective values of human lives or financial payoffs by means of structurally identical computational models. Correlating isomorphic model variables from both domains with brain activity reveals specific patterns of neural activity that selectively represent values in the moral (in the rTPJ) or financial (in the vmPFC) domain. Thus, our findings show that human lives and money are valued in distinct neural currencies, supporting theoretical proposals that human moral behavior is guided by processes that are distinct from those underlying behavior driven by personal material benefit.

scholarly journals Neuro-computational foundations of moral preferences

2021 ◽  
Author(s):  
Giuseppe Ugazio ◽  
Marcus Grueschow ◽  
Rafael Polania ◽  
Claus Lamm ◽  
Philippe Tobler ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Human Life ◽  
Functional Magnetic Resonance ◽  
Moral Value ◽  
Ventral Medial Prefrontal Cortex ◽  
Neural Representations ◽  
Neural Processes ◽  
Behavioral Paradigm ◽  
Decision Mechanisms

Abstract Moral preferences pervade many aspects of our lives, dictating how we ought to behave, whom we can marry and even what we eat. Despite their relevance, one fundamental question remains unanswered: where do individual moral preferences come from? It is often thought that all types of preferences reflect properties of domain-general neural decision mechanisms that employ a common ‘neural currency’ to value choice options in many different contexts. This view, however, appears at odds with the observation that many humans consider it intuitively wrong to employ the same scale to compare moral value (e.g. of a human life) with material value (e.g. of money). In this paper, we directly test if moral subjective values are represented by similar neural processes as financial subjective values. In a study combining functional magnetic resonance imaging with a novel behavioral paradigm, we identify neural representations of the subjective values of human lives or financial payoffs by means of structurally identical computational models. Correlating isomorphic model variables from both domains with brain activity reveals specific patterns of neural activity that selectively represent values in the moral (right temporo-parietal junction) or financial (ventral-medial prefrontal cortex) domain. Intriguingly, our findings show that human lives and money are valued in (at least partially) distinct neural currencies, supporting theoretical proposals that human moral behavior is guided by processes that are distinct from those underlying behavior driven by personal material benefit.

scholarly journals Excitatory TMS Boosts Memory Representations

2018 ◽  
Author(s):  
Wei-Chun Wang ◽  
Erik A. Wing ◽  
David L.K. Murphy ◽  
Bruce M. Luber ◽  
Sarah H. Lisanby ◽  
...  
Keyword(s):  
Cognitive Enhancement ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Neural Mechanisms ◽  
Temporal Memory ◽  
Memory Functioning ◽  
Neural Representations ◽  
Memory Representations ◽  
Science Investigations ◽  
Univariate Analyses

AbstractBrain stimulation technologies have seen increasing application in basic science investigations, specifically towards the goal of improving memory functioning. However, proposals concerning the neural mechanisms underlying cognitive enhancement often rely on simplified notions of excitation and, most applications examining the effects of transcranial magnetic stimulation (TMS) on functional neuroimaging measures have been limited to univariate analyses of brain activity. We present here analyses using representational similarity analysis (RSA) and encoding-retrieval similarity (ERS) analysis in order to quantify the effect of TMS on memory representations. To test whether an increase in local excitability in PFC can have measurable influences on upstream representations in earlier temporal memory regions, we compared 1Hz and 5Hz stimulation to the left dorsolateral PFC. We found that 10 minutes of 5Hz rTMS, relative to 1Hz, had multiple effects on neural representations: 1) greater RSA during both encoding and retrieval, 2) greater ERS across all items, and, critically, 3) increasing ERS in MTL with increasing univariate activity in DLPFC, and greater functional connectivity for hits than misses between these regions. These results provide the first evidence of rTMS enhancing semantic representations and strengthen the idea that rTMS may affect the reinstatement of previously experienced events in upstream regions.

scholarly journals Object novelty and value coding segregate across functionally connected brain networks

2019 ◽  
Author(s):  
Ali Ghazizadeh ◽  
MohammadAmin Fakharian ◽  
Arash Amini ◽  
Whitney Griggs ◽  
David A. Leopold ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Networks ◽  
Temporal Cortex ◽  
Common Currency ◽  
Activation Dynamics ◽  
Fractal Patterns ◽  
The Common ◽  
Ventral Temporal Cortex ◽  
Value Coding ◽  
The Brain

AbstractNovel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain activity to fractal patterns varying in either novelty or value dimensions in the context of functionally connected brain networks determined at rest. Results show unique combinations of novelty and value coding across the brain networks. Networks in the ventral temporal cortex and in the parietal cortex showed preferential coding of novelty and value dimensions, respectively, while a wider network composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, responded to both dimensions with similar activation dynamics. Our results support emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

KONSEP DAN IMPLEMENTASI ETIKA ISLAM DALAM DUNIA BISNIS

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Nurul Fatima Hasan
Keyword(s):  
Business Ethics ◽  
Business Ethic ◽  
Human Life ◽  
Ethical Dimension ◽  
Moral Value ◽  
Business People ◽  
Islamic Business Ethics ◽  
The Right

Indeed, in terms of the whole implementation of life has been arranged in the view of Islamic teachings to regulate all human life including in relation to the implementation of the economy and business. Islam does not allow any person to work haphazardly to achieve his/her goals and desires by justifying any means such as committing fraud, cheating, false vows, usury, and any other vanity deeds. But, Islam has given a boundary or line between the allowable and the unlawful, the right and wrong and the lawful and the unlawful. These limits or dividing lines are known as ethics. Behavior in business or trade is also not escaped from the moral value or business ethics values. Islamic business ethics is of which adheres to the principle of unity, equilibrium principle, freewill principle, responsibility principle, It is important for business people to integrate that ethical dimension into the framework or scope of the business. Keyword: Ethics, Business Ethics, Islamic Business Ethic.

What Theology Should and Should Not Learn from the Social Sciences About the Common Good

2017 ◽  
Author(s):  
Mary L. Hirschfeld
Keyword(s):  
Social Sciences ◽  
Common Good ◽  
Human Life ◽  
Social Thought ◽  
Extensive Literature ◽  
Human Flourishing ◽  
Catholic Social Thought ◽  
The Common Good ◽  
The Social ◽  
The Common

There are two ways to answer the question, What can Catholic social thought learn from the social sciences about the common good? A more modern form of Catholic social thought, which primarily thinks of the common good in terms of the equitable distribution of goods like health, education, and opportunity, could benefit from the extensive literature in public policy, economics, and political science, which study the role of institutions and policies in generating desirable social outcomes. A second approach, rooted in pre-Machiavellian Catholic thought, would expand on this modern notion to include concerns about the way the culture shapes our understanding of what genuine human flourishing entails. On that account, the social sciences offer a valuable description of human life; but because they underestimate how human behavior is shaped by institutions, policies, and the discourse of social science itself, their insights need to be treated with caution.

scholarly journals Neural alignment predicts learning outcomes in students taking an introduction to computer science course

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  
Keyword(s):  
Computer Science ◽  
Learning Outcomes ◽  
Brain Activity ◽  
Activity Patterns ◽  
Real Life ◽  
Final Exam ◽  
Neural Representations ◽  
Real Life Setting ◽  
The Right ◽  
Mri Study

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.

scholarly journals A computational reward learning account of social media engagement

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Björn Lindström ◽  
Martin Bellander ◽  
David T. Schultner ◽  
Allen Chang ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Social Media ◽  
Human Behavior ◽  
Computational Models ◽  
Average Rate ◽  
Human Life ◽  
Modern Human ◽  
Reward Learning ◽  
Learning Mechanisms ◽  
Social Media Engagement ◽  
Social Rewards

AbstractSocial media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (likes), portraying the online world as a Skinner Box for the modern human. Yet despite such portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. Here, we apply a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyze over one million posts from over 4000 individuals on multiple social media platforms, using computational models based on reinforcement learning theory. Our results consistently show that human behavior on social media conforms qualitatively and quantitatively to the principles of reward learning. Specifically, social media users spaced their posts to maximize the average rate of accrued social rewards, in a manner subject to both the effort cost of posting and the opportunity cost of inaction. Results further reveal meaningful individual difference profiles in social reward learning on social media. Finally, an online experiment (n = 176), mimicking key aspects of social media, verifies that social rewards causally influence behavior as posited by our computational account. Together, these findings support a reward learning account of social media engagement and offer new insights into this emergent mode of modern human behavior.

scholarly journals Effortless Retaliation: the Neural Dynamics of Interpersonal Intentions in a Chicken Game Using Brain-Computer Interface

2021 ◽  
Author(s):  
Yiwen Wang ◽  
Yuxiao Lin ◽  
Chao Fu ◽  
Zhihua Huang ◽  
Rongjun Yu ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Computer Interface ◽  
Neural Mechanisms ◽  
Computer Interface ◽  
Neural Dynamics ◽  
Neural Signals ◽  
Chicken Game ◽  
Common Response ◽  
Tit For Tat ◽  
Novel Method

Abstract The desire for retaliation is a common response across a majority of human societies. However, the neural mechanisms underlying aggression and retaliation remain unclear. Previous studies on social intentions are confounded by low-level response related brain activity. Using an EEG-based brain-computer interface (BCI) combined with the Chicken Game, our study examined the neural dynamics of aggression and retaliation after controlling for nonessential response related neural signals. Our results show that aggression is associated with reduced alpha event-related desynchronization (ERD), indicating reduced mental effort. Moreover, retaliation and tit-for-tat strategy use are also linked with smaller alpha-ERD. Our study provides a novel method to minimize motor confounds and demonstrates that choosing aggression and retaliation is less effortful in social conflicts.

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